Information processing device, information processing method, and program thereof

ABSTRACT

An information processing device processes information related to a printing process performed by an inkjet device drawing an image onto a fabric and at least one of a pre-processing device performing pre-processing on the fabric before an image is drawn and a post-processing device performing post-processing on the fabric after an image is drawn, the information processing device including an acquisition unit acquiring image data and original image data, the image data being obtained by digitizing a printed fabric as an image, the original image data being original data of an image drawn on the fabric; a storage unit storing derivation data for deriving, based on the image data and the original image data, a recommended parameter for at least one of the pre-processing device and the post-processing device; and a control unit deriving, based on the derivation data, the recommended parameter from the image data and the original image data.

The present application is based on, and claims priority from JPApplication Serial Number 2020-182869, filed Oct. 30, 2020, thedisclosure of which is hereby incorporated by reference herein in itsentirety.

BACKGROUND 1. Technical Field

The present disclosure relates to an information processing device, aninformation processing method, and a program thereof.

2. Related Art

JP-A-2004-174943 describes a printing printer system for performing aprinting process on a fabric. The printing printer system includes, forexample, an inkjet device, a pre-processing device, and apost-processing device.

In the printing printer system, it is preferable that the differencebetween the image quality of a post-printing image printed on the fabricby the printing process and the image quality of original image datawhich is original data of the post-printing image is small. Thus, a usersets a parameter of the pre-processing device and post-processing deviceso that the difference between the image quality of the post-printingimage and the image quality of the original image data becomes small.However, depending on the user, the correlation between the parameter ofthe pre-processing device and post-processing device and the imagequality may not be known. In this case, by repeating the printingprocess while changing the parameters of the pre-processing device andpost-processing device, the user needs to set a parameter that makes thedifference between the image quality of the post-printing image and theimage quality of the original image data small. As a result, operationof the user may become cumbersome.

SUMMARY

An information processing device for solving the above-describedproblems includes an information processing device configured to processinformation related to a printing process performed by an inkjet deviceand at least one of a pre-processing device and a post-processingdevice, the inkjet device being configured to draw an image bydischarging ink onto a fabric, the pre-processing device beingconfigured to perform pre-processing on the fabric before an image isdrawn, the post-processing device being configured to performpost-processing on the fabric after an image is drawn, the informationprocessing device including an acquisition unit configured to acquireimage data and original image data, the image data being obtained bydigitizing, as an image, the fabric on which the printing process isperformed, the original image data being original data of an image drawnon the fabric, a storage unit configured to store derivation data forderiving, based on the image data and the original image data, arecommended parameter for at least one of the pre-processing device andthe post-processing device, and a control unit configured to derive,based on the derivation data, the recommended parameter from the imagedata and the original image data.

An information processing method for solving the above-describedproblems includes an information processing method for processinginformation related to a printing process performed by an inkjet deviceand at least one of a pre-processing device and a post-processingdevice, the inkjet device being configured to draw an image bydischarging ink onto a fabric, the pre-processing device beingconfigured to perform pre-processing on the fabric before an image isdrawn, the post-processing device being configured to performpost-processing on the fabric after an image is drawn, the methodincluding acquiring image data and original image data, the image databeing obtained by digitizing, as an image, the fabric on which theprinting process is performed, the original image data being originaldata of an image drawn on the fabric, and deriving, based on derivationdata, a recommended parameter from the image data and the original imagedata, the derivation data being data for deriving, based on the imagedata and the original image data, the recommended parameter for at leastone of the pre-processing device and the post-processing device.

A non-transitory computer-readable storage medium for solving theproblems described above includes a non-transitory computer-readablestorage medium storing a program for causing a computer to processinformation related to a printing process performed by an inkjet deviceand at least one of a pre-processing device and a post-processingdevice, the inkjet device being configured to draw an image bydischarging ink onto a fabric, the pre-processing device beingconfigured to perform pre-processing on the fabric before an image isdrawn, the post-processing device being configured to performpost-processing on the fabric after an image is drawn, wherein theprogram causes the computer to acquire image data and original imagedata, the image data being obtained by digitizing, as an image, thefabric on which the printing process is performed, the original imagedata being original data of an image drawn on the fabric, and derive,based on derivation data, a recommended parameter from the image dataand the original image data, the derivation data being data forderiving, based on the image data and the original image data, therecommended parameter for at least one of the pre-processing device andthe post-processing device.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating a printing system.

FIG. 2 is a flowchart illustrating a procedure of a printing process.

FIG. 3 is a block diagram illustrating one exemplary embodiment of aninformation processing device.

FIG. 4 is a flowchart illustrating operation of the informationprocessing device.

FIG. 5 is a flowchart illustrating operation of a server.

DESCRIPTION OF EXEMPLARY EMBODIMENTS

Hereinafter, an exemplary embodiment of an information processing devicewill be described with reference to the drawings. The informationprocessing device is a device for processing information related to aprinting process performed by a printing system. First, the printingsystem is described.

As illustrated in FIG. 1 , a printing system 10 is constituted by apre-processing device 11, an inkjet device 12, and a post-processingdevice 13, for example. The printing system 10 may be constituted by thepre-processing device 11 and the inkjet device 12, or may be constitutedby the inkjet device 12 and the post-processing device 13. That is, theprinting system 10 includes the inkjet device 12 and at least one of thepre-processing device 11 and the post-processing device 13.

The printing system 10 is a system for performing the printing processon a fabric 99. The printing system 10 performs the printing process onthe fabric 99 by three processes, for example, pre-processing, drawingprocessing, and post-processing. The pre-processing is performed by thepre-processing device 11. The drawing processing is performed by theinkjet device 12. The post-processing is performed by thepost-processing device 13.

The printing process is achieved by performing processing on the fabric99 in an order of the pre-processing, drawing processing, andpost-processing, for example. When the printing system 10 is constitutedby the pre-processing device 11 and the inkjet device 12, the printingprocess is achieved by the pre-processing and drawing processing. Wherethe printing system 10 is constituted by the inkjet device 12 and thepost-processing device 13, the printing process is achieved by thedrawing processing and post-processing. That is, the printing process isachieved by the drawing processing and at least one of thepre-processing and post-processing.

The printing process may be achieved by a device owned by one user or bycooperation with a device owned by other users. For example, thepre-processing device 11 owned by a first user and the inkjet device 12and the post-processing device 13 owned by a second user different fromthe first user may achieve the printing process. In this case, the firstuser performs the pre-processing on the fabric 99, and the second userperforms the drawing processing and post-processing on the fabric 99,whereby the printing process is achieved.

In the printing system 10, coordination may or may not be taken betweenthe devices of the pre-processing device 11, the inkjet device 12, andthe post-processing device 13. That is, the pre-processing device 11,the inkjet device 12, and the post-processing device 13 may exchangeinformation to each other or may not exchange information to each other.

The pre-processing device 11 is a device that performs thepre-processing on the fabric 99 before an image is drawn. Thepre-processing is a process performed before the drawing processing. Thepre-processing device 11 includes, for example, an application unit 14,a correcting unit 15, and a pre-processing drying unit 16.

The application unit 14 is configured to apply pre-processing liquid tothe fabric 99. The application unit 14 includes a storage tank thatstores the pre-processing liquid, for example. For example, thepre-processing liquid is applied to the fabric 99 by passing the fabric99 through the storage tank. The pre-processing liquid is liquid forfixing ink to the fabric 99 in the drawing processing. Thepre-processing liquid affects hydrophilicity of the fabric 99 withrespect to the ink.

The correction unit 15 is configured to correct the fabric 99. Thecorrection unit 15 stretches warp yarns or weft yarns constituting thefabric 99 by applying force to the fabric 99, for example. This allowsthe fabric 99 to be corrected. The correction unit 15 includes, forexample, a roller where the fabric 99 is wound, a pin, a clip, etc. thathold both sides of the fabric 99. The correction unit 15 is a so-calledtenter. When the pre-processing liquid is applied to the fabric 99,shrinkage may occur in the fabric 99. As such, the correction unit 15corrects the fabric 99 by stretching the fabric 99.

The pre-processing drying unit 16 is configured to dry the fabric 99.The pre-processing drying unit 16 is a drying unit included in thepre-processing device 11. The pre-processing drying unit 16 dries thefabric 99 to which the pre-processing liquid has been applied, forexample, by heating the fabric 99. The pre-processing drying unit 16includes a heater, for example.

The inkjet device 12 is a device that performs the drawing processing onthe fabric 99. The drawing processing is a process for drawing an imageon the fabric 99. The inkjet device 12 discharges the ink onto thefabric 99 to draw the image. The inkjet device 12 draws design imagessuch as pictures, patterns, etc., for example. The inkjet device 12includes, for example, a transport unit 17, a head 18, and a carriage19.

The transport unit 17 is configured to transport the fabric 99. Thetransport unit 17 is, for example, a belt, a roller, etc. The transportunit 17 intermittently transports the fabric 99, for example.

The head 18 is configured to discharge the ink onto the fabric 99. Thehead 18 has a nozzle 21 for discharging the ink. A nozzle resolution ofthe head 18 is 600 dpi, for example. As such, the head 18 can draw theimage with a resolution of 600 dpi on the fabric 99.

The head 18 is mounted in the carriage 19. The carriage 19 is configuredto perform scanning on the fabric 99. The head 18 discharges the inkonto the fabric 99 while the carriage 19 performs scanning, therebydrawing or printing an image on the fabric 99. Thus, the inkjet device12 is a so-called serial type printer.

The carriage 19 is configured to be mountable with a container 22accommodating the ink, for example. The container 22 is an inkcartridge, for example. When the container 22 is attached to thecarriage 19, the ink is supplied from the container 22 to the head 18. Acode 23 for indicating the type of ink to be accommodated is attached tothe container 22. The code 23 is, for example, a barcode.

The container 22 is not limited to being mounted in the carriage 19 andmay be coupled to the head 18, for example, via a tube. The container 22may be, for example, a container for refilling an accommodationcontainer separately provided by the inkjet device 12, a so-called inkbottle.

The post-processing device 13 is a device that performs thepost-processing on the fabric 99 after the image has been drawn. Thepost-processing is a process performed after the drawing processing. Thepost-processing device 13 includes, for example, a post-processingdrying unit 24, a steam unit 25, and a cleaning unit 26.

The post-processing drying unit 24 is configured to dry the fabric 99.The post-processing drying unit 24 is a drying unit included in thepost-processing device 13. The post-processing drying unit 24 dries thefabric 99 to which the ink has been discharged, for example, by heatingthe fabric 99. The post-processing drying unit 24 includes, for example,a heater. The post-processing drying unit 24 may be the same drying unitas the pre-processing drying unit 16. In other words, the pre-processingdevice 11 and the post-processing device 13 may share a drying unit.

The steam unit 25 is configured to supply hot steam to the fabric 99. Asthe steam unit 25 heats the fabric 99 with steam, the fixing of the inkdischarged onto the fabric 99 is promoted.

The cleaning unit 26 is configured to clean the fabric 99. The cleaningunit 26 includes, for example, a cleaning tank that stores cleaningliquid. For example, the fabric 99 is cleaned by passing the fabric 99through cleaning liquid. The cleaning liquid is, for example, water.When the fabric 99 is cleaned, ink, pre-processing liquid, etc. that arenot fixed to the fabric 99 are removed from the fabric 99.

The printing system 10 performs the printing process, for example, alongthe flowchart illustrated in FIG. 2 . The printing process is initiatedby the user, for example.

As illustrated in FIG. 2 , the printing system 10 first applies thepre-processing liquid to the fabric 99 by the application unit 14 instep S11.

The printing system 10 corrects the fabric 99 by the correction unit 15in step S12.

The printing system 10 dries the fabric 99 by the pre-processing dryingunit 16 in step S13.

The printing system 10 discharges the ink from the head 18 onto thefabric 99 transported by the transport unit 17 in step S14 to draw animage on the fabric 99. At this time, the carriage 19 is driven alongwith the head 18.

The printing system 10 dries the fabric 99 by the post-processing dryingunit 24 in step S15. At this time, the printing system 10 dries thefabric 99 to an extent that migration of the ink discharged onto thefabric 99 is suppressed. That is, in step S15, the printing system 10dries the fabric 99 to an extent that a surface of the ink dischargedonto the fabric 99 is dried.

The printing system 10 supplies steam to the fabric 99 by the steam unit25 in step S16.

The printing system 10 cleans the fabric 99 with the cleaning unit 26 instep S17.

The printing system 10 dries the fabric 99 by the post-processing dryingunit 24 in step S18. In step S18, unlike step S15, the printing system10 completely dries the fabric 99. As a result, the fabric 99 wetted bythe cleaning liquid is dried. Upon completion of the process of stepS18, the printing process is complete.

Next, the information processing device 30 will be described.

As illustrated in FIG. 1 , the information processing device 30 iselectrically coupled to the printing system 10. For example, theinformation processing device 30 is electrically coupled to thepre-processing device 11, the inkjet device 12, and the post-processingdevice 13. As such, the information processing device 30 can exchangeinformation with the pre-processing device 11, the inkjet device 12, andthe post-processing device 13.

The information processing device 30 is a device for processinginformation related to the printing process. The information processingdevice 30 may also serve as a control device for controlling theprinting system 10. In this case, the user controls the printing system10 via the information processing device 30. The information processingdevice 30 controls a printing parameter related to the printing processof the printing system 10. The printing parameter includes, for example,a pre-processing parameter related to the pre-processing of thepre-processing device 11, a drawing processing parameter related to thedrawing processing of the inkjet device 12, a post-processing parameterfor the post-processing of the post-processing device 13, etc.

The pre-processing parameter includes, for example, an amount of thepre-processing liquid applied by the application unit 14, an applicationtime of the pre-processing liquid by the application unit 14, a type ofthe pre-processing liquid, a direction of force applied by thecorrection unit 15 to the fabric 99, an amount of the force applied bythe correction unit 15 to the fabric 99, a time the correction unit 15applies the force to the fabric 99, a drying time of the pre-processingdrying unit 16, a drying temperature of the pre-processing drying unit16, etc.

The drawing processing parameter includes, for example, a transportspeed of the fabric 99 by the transport unit 17, a distance between thehead 18 and the fabric 99, a movement speed of the carriage 19, a numberof passes of the carriage 19, a printing mode, a printing directionindicating unidirectional printing or bi-directional printing, etc.

The post-processing parameter includes, for example, a drying time ofthe post-processing drying unit 24, a drying temperature of thepost-processing drying unit 24, a temperature of the steam supplied bythe steam unit 25, a supply time of steam by the steam unit 25, acleaning time by the cleaning unit 26, a temperature of the cleaningwater, etc.

The information processing device 30 is, for example, a personalcomputer. The information processing device 30 may be configured as acircuit including α: one or more processors for performing variousprocesses according to a computer program, β: one or more dedicatedhardware circuits such as application-specific integrated circuits thatperform at least some processing of various processes, or γ:combinations thereof. The processor includes a CPU and a memory such asa RAM and a ROM, and the memory stores a program code or an instructionconfigured to cause the CPU to execute a process. The memory, i.e. acomputer-readable medium, includes any readable medium that can beaccessed by a general-purpose or dedicated computer.

As illustrated in FIG. 3 , the information processing device 30includes, for example, an input unit 31, an output unit 32, anacquisition unit 33, a control unit 34, a storage unit 35, atransmission unit 36, and a reception unit 37.

The input unit 31 is an interface for the user to input data into theinformation processing device 30. Thus, the input unit 31 is coupled toan input device 38 such as a mouse, keyboard, or touch panel, forexample. The user inputs data to the information processing device 30through the input unit 31 by manipulating the input device 38. The datainput through the input unit 31 is stored in the storage unit 35, forexample.

The user inputs, for example, client data indicating information about aclient through the input unit 31. The information about the client is,for example, a client country, a client name, etc. The user inputsapplication data indicating, for example, information related to theapplication of the fabric 99 to which the printing process has beenperformed through the input unit 31. The information related to theapplication is information representing an application such as, forexample, female clothing, child clothing, interior, etc. The user mayinput other information to the information processing device 30 as datathrough the input unit 31, not limited to the client data and theapplication data.

The output unit 32 is an interface for outputting data from theinformation processing device 30. The output unit 32 is coupled to anoutput device 39 such as a display, a speaker, etc. For example, theuser can grasp the data output from the information processing device 30through the output unit 32 by ascertaining the output device 39.

The acquisition unit 33 is an interface for acquiring data from theoutside. The acquisition unit 33 is coupled to, for example, an imagecapturing device 41, a weighing device 42, a reading device 43, atemperature and humidity meter 44, a network 45, the printing system 10,etc. In addition, the acquisition unit 33 may be coupled to a storagemedium such as, for example, a USB flash drive, a memory card, etc. Theacquisition unit 33 acquires data from the coupled object. The dataacquired by the acquisition unit 33 is stored in the storage unit 35,for example.

The acquisition unit 33 acquires data indicating information related tothe printing process, for example. When the printing system 10 performsthe printing process, the acquisition unit 33 acquires, from theprinting system 10, a printing parameter set to the pre-processingdevice 11, the inkjet device 12, and the post-processing device 13, forexample.

The image capturing device 41 is a device that captures the fabric 99 asan image. The image capturing device 41 is, for example, a camera, ascanner, etc. The image capturing device 41 captures the fabric 99 as animage by capturing or scanning the fabric 99. At this time, the imagecapturing device 41 generates image data obtained by digitizing thefabric 99 as an image. Accordingly, the acquisition unit 33 acquires theimage data obtained by digitizing the fabric 99 as an image through theimage capturing device 41.

The user appropriately captures the fabric 99 as an image by using theimage capturing device 41. For example, by the image capturing device41, the user captures, as an image, the fabric 99 before the printingprocess is performed, the fabric 99 after the printing process isperformed, the fabric 99 after the pre-processing is performed andbefore the drawing processing is performed, and the fabric 99 after thedrawing processing is performed and before the post-processing isperformed, etc. For example, the user captures the fabric 99 as an imageat timings before the printing process is performed, after the printingprocess is performed, after the pre-processing is performed and beforethe drawing processing is performed, and after the drawing processing isperformed and before the post-processing is performed. Thus, the imagecapturing device 41 generates pre-printing image data obtained bydigitizing the fabric 99 before the printing process is performed as animage, post-printing image data obtained by digitizing the fabric 99after the printing process is performed as an image, pre-drawing imagedata obtained by digitizing the fabric 99 after the pre-processing isperformed and before the drawing processing is performed as an image,and post-drawing image data obtained by digitizing the fabric 99 beforethe post-processing is performed and after the drawing processing isperformed as an image. Accordingly, the acquisition unit 33 can acquirethe pre-printing image data, post-printing image data, pre-drawing imagedata, and post-drawing image data as image data obtained by digitizingthe fabric 99 as an image. The acquisition unit 33 of the presentexample acquires at least the post-printing image data among the imagedata.

The image capturing device 41 digitizes the fabric 99 as an image at aresolution that is greater than or equal to a resolution of the imagedrawn by the inkjet device 12, for example. In this case, the image datais data obtained by digitization at a resolution that is greater than orequal to the resolution of the image drawn on the fabric 99. In thismanner, the image data suitable for image analysis described later canbe obtained. The image capturing device 41 may capture the fabric 99 ina full color image, may capture the fabric 99 in a monochrome image, ormay capture the fabric 99 in a greyscale image.

The user may capture a front surface of the fabric 99 and a back surfaceof the fabric 99 as an image when capturing the fabric 99 as an image bythe image capturing device 41. In this case, the image data includes thedata obtained by digitizing the front surface of the fabric 99 and thedata obtained by digitizing the back surface of the fabric 99.

The user may capture an image in a state where the fabric 99 isstretched and an image in a state where the fabric 99 is not stretchedwhen capturing the fabric 99 as an image by the image capturing device41. In this case, the image data includes the data obtained bydigitizing the fabric 99 in a state where the fabric 99 is stretched andthe data obtained by digitizing the fabric 99 in a state where thefabric 99 is not stretched. For example, the user captures the fabric 99as an image while stretching the fabric 99 by a hand thereof. The usermay stretch the fabric 99 in a direction along the warp yarns, maystretch the fabric 99 in a direction along the weft yarns, or maystretch the fabric 99 diagonally relative to the warp yarns and weftyarns.

The weighing device 42 is a device for weighing the fabric 99. The usermeasures a weight per unit area of the fabric 99 by using the weighingdevice 42. As a result, the acquisition unit 33 acquires basis weightdata indicating the weight per unit area of the fabric 99 through theweighing device 42.

The reading device 43 is a device for reading the code 23 attached tothe container 22, for example. The reading device 43 is, for example, areader. The user causes the reading device 43 to read the code 23attached to the container 22. The acquisition unit 33 acquires thecorresponding ink data with the code 23 read by the reading device 43,for example, by referencing a database stored in the storage unit 35.The ink data is data indicating a type of ink such as, for example,reaction ink, dispersed ink, and acidic ink. The acquisition unit 33acquires ink data indicating the type of ink accommodated in thecontainer 22 by reading the code 23 attached to the container 22 by thereading device 43.

The temperature and humidity meter 44 is a sensor that measurestemperature and humidity. The temperature and humidity meter 44 measuresthe temperature and humidity of an environment in which thepre-processing device 11, the inkjet device 12, and the post-processingdevice 13 are installed. As a result, the acquisition unit 33 acquirestemperature and humidity data indicating the temperature and humidity ofthe environment in which the printing system 10 is installed.

The acquisition unit 33 may acquire data the through the network 45based on the data input from the user. For example, based on dataindicating a model number of the fabric 99 input from the user, theacquisition unit 33 may acquire fabric data indicating information aboutthe fabric 99 from the database on the network 45. The fabric data isdata indicating the feature value of the fabric 99, such as a thickness,density, and surface roughness of yarns constituting the fabric 99. Thefabric data may be data obtained by quantifying the feature value of thefabric 99, or may be data indicating the type of fabric 99 classifiedbased on the feature value of the fabric 99.

For example, based on data indicating a model number of the device inputfrom the user, the acquisition unit 33 may acquire device dataindicating information about the device from the database on the network45. The information about the device includes information related tospecifications, settings, etc. of the device. In other words, theacquisition unit 33 may acquire the device data indicating the deviceinformation of the pre-processing device 11. The acquisition unit 33 mayacquire the device data indicating the device information of the inkjetdevice 12. The acquisition unit 33 may acquire the device dataindicating the device information of the post-processing device 13.

The acquisition unit 33 acquires original image data, which is originaldata of the image drawn on the fabric 99 by the inkjet device 12, forexample, from the storage medium, the network 45, etc. That is, theinkjet device 12 draws an image on the fabric 99 based on the originalimage data. The original image data can be the original data of theimage drawn by the drawing processing. The original image data is, forexample, data provided to the user from the client.

Without being limited to the image data, basis weight data, ink data,fabric data, device data, printing parameter, original image data, theacquisition unit 33 may acquire other data. The acquisition unit 33 mayacquire the data through the network 45 or may acquire the data throughthe input unit 31. The example described above is merely an example ofthe type of data acquired by the acquisition unit 33 and the means foracquiring the data. Accordingly, the acquisition unit 33 may acquire thedata other than the type described above, or may acquire the data by ameans other than the means described above.

The acquisition unit 33 may acquire status data indicating a usagecondition of the pre-processing device 11, the inkjet device 12, and thepost-processing device 13. The status data is data indicating the usagecondition including environmental information of the pre-processingdevice 11, the inkjet device 12, and the post-processing device 13.

The status data is data indicating, for example, an operation time,which is the time elapsed since the pre-processing device 11, the inkjetdevice 12, and the post-processing device 13 have been in operation, thetemperature and humidity of the environment in which the printing system10 is installed, the water quality of the cleaning liquid used in thecleaning unit 26, etc. The status data includes the temperature andhumidity data as data indicating the environmental information. Theacquisition unit 33 acquires, as status data, for example, operatingdata indicating the operation time of each device from the printingsystem 10. The acquisition unit 33 acquires water quality dataindicating the water quality of the cleaning liquid by, for example,inputting the water quality of the cleaning fluid through the input unit31 as data indicating the environmental information.

The acquisition unit 33 may acquire altitude data indicating an altitudeat which the pre-processing device 11, the inkjet device 12, and thepost-processing device 13 are installed as data indicating theenvironmental information. The acquisition unit 33 acquires the altitudedata by, for example, inputting the altitude at which the pre-processingdevice 11, the inkjet device 12, and the post-processing device 13 areinstalled, through the input unit 31. The acquisition unit 33 mayacquire the altitude data from the network 45, or may acquire thealtitude data by performing conversion from a barometer coupled to theacquisition unit 33.

The control unit 34 is, for example, the CPU described above. Thecontrol unit 34 comprehensively controls the information processingdevice 30. The control unit 34 controls various configurations byexecuting a program stored in the storage unit 35. The control unit 34may control the printing system 10, for example. The control unit 34controls the printing system 10, for example, by transmitting theprinting parameter to the printing system 10.

The storage unit 35 is, for example, the memory described above. Inaddition to the program executed by the control unit 34, the storageunit 35 stores, for example, data input through the input unit 31, dataoutput through the output unit 32, data acquired by the acquisition unit33, etc. The storage unit 35 stores a data set 46 and derivation data47, for example.

The storage unit 35 stores one or more data sets 46. The data set 46 isa set of a plurality of data for one printing process. The data set 46includes data input through the input unit 31, data acquired through theacquisition unit 33, etc. In other words, the storage unit 35 storesdata input through the input unit 31, data acquired by the acquisitionunit 33, etc. as the data set 46. The storage unit 35 stores the dataset 46 illustrated in Table 1, for example.

TABLE 1 Original Printing Post-printing Client data Fabric Data Ink dataimage data parameter image data First Client A Fabric A Dispersed . . .. . . . . . data set ink Second Client A Fabric A Dispersed . . . . . .. . . data set ink Third Client A Fabric B Reaction . . . . . . . . .data set ink Fourth Client A Fabric B Reaction . . . . . . . . . dataset ink . . . . . . . . . . . . . . . . . . . . .

As illustrated in Table 1, the data set 46 is associated with aplurality of data such as, for example, the client data, fabric data,ink data, original image data, printing parameter, post-printing imagedata, etc. Table 1 lists the client data, fabric data, ink data,original image data, printing parameter, and post-printing image data,but actually, the data input through the input unit 31 and other dataacquired by the acquisition unit 33 are associated, such as theapplication data, basis weight data, status data, etc. described above.The data set 46 is a set of various data and various parametersassociated with one printing process.

The derivation data 47 is data for deriving the recommended parameterfor at least one of the pre-processing device 11 and the post-processingdevice 13 based on the post-printing image data and the original imagedata. The derivation data 47 is data defining a learned model learned bymachine learning. The derivation data 47 is data for deriving therecommended parameter for at least one of the pre-processing device 11and the post-processing device 13 when the post-printing image data andthe original image data are input.

The derivation data 47 may be data for deriving the recommendedparameter for the inkjet device 12 based on the post-printing image dataand the original image data. The derivation data 47, for example, may bedata deriving the recommended parameter for the inkjet device 12 relatedto the post-printing image data and the original image data, in additionto the recommended parameter for at least one of the pre-processingdevice 11 and the post-processing device 13.

The recommended parameter is a printing parameter recommended forobtaining predetermined image quality. The recommended parameter is, forexample, a printing parameter recommended so that the difference betweenthe image quality of the original image data and the image quality ofthe post-printing image data is small. Therefore, the recommendedparameter may be, for example, a printing parameter recommended forobtaining the image quality equivalent to the original image data, or aprinting parameter recommended for obtaining image quality such that theclient evaluates that the image quality is sufficient.

The derivation data 47, which is data defining the learned model, isgenerated, for example, by inputting the data set 46 described aboveinto a model for machine learning and by causing the model to learn thedata set 46. Such a learned model can be generated, for example, by aserver 50 calculating based on the data set 46.

The transmission unit 36 is an interface for transmitting data to theserver 50. For example, transmission unit 36 transmits the data set 46to the server 50.

The reception unit 37 is an interface for receiving data from the server50. For example, the reception unit 37 receives the derivation data 47from the server 50.

The information processing device 30 performs operation along aflowchart illustrated in FIG. 4 , for example. The series of processesillustrated in FIG. 4 is initiated by the user, for example. The seriesof processes illustrated in FIG. 4 is executed by the control unit 34.

As illustrated in FIG. 4 , first, in step S21, the control unit 34acquires the post-printing image data and the original image data by theacquisition unit 33. Accordingly, step S21 is performed after theprinting process by the printing system 10 is performed. Thepost-printing image data acquired in step S21 is image data obtained bydigitizing the post-printing image obtained by the printing process.

In step S21, the control unit 34 may acquire the client data, fabricdata, ink data, etc. in addition to the post-printing image data and theoriginal image data. At this time, without being limited to acquiringdata from an external device such as the input device 38, the imagecapturing device 41, etc., for example, the control unit 34 may acquiredata from the data set 46 stored in the storage unit 35.

The control unit 34 inputs the post-printing image data and the originalimage data into the learned model in step S22. That is, the control unit34 derives the recommended parameter from the post-printing image dataand the original image data based on the derivation data 47.

In step S23, the control unit 34 outputs the recommended parameterthrough the output unit 32. When the recommended parameter is outputthrough the output unit 32, the user can grasp the printing parameterrecommended for obtaining predetermined image quality. Specifically, theuser can grasp the printing parameter recommended for bringing the imagequality of the image drawn on the fabric 99 closer to the image qualityof the original image data. This allows the user to take advantage ofthe recommended parameter output as an indicator to obtain thepredetermined image quality.

Upon terminating the process in step S23, the control unit 34 terminatesthe series of processes illustrated in FIG. 4 . As described above, theinformation processing method for processing information related to theprinting process includes acquiring the post-printing image data and theoriginal image data, and deriving the recommended parameter from thepost-printing image data and the original image data based on thederivation data 47. The information processing method is implemented,for example, by causing a computer to execute a program. This programmay be stored in the storage unit 35, or may be stored in the storagemedium. The control unit 34 executes the information processingdescribed above by reading the program.

Next, the server 50 will be described.

As illustrated in FIG. 3 , the server 50 is electrically coupled to theinformation processing device 30. Similar to the information processingdevice 30, the server 50 may be configured as a circuit including α: oneor more processors for performing various processes according to acomputer program, β: one or more dedicated hardware circuits such asapplication-specific integrated circuits that perform at least someprocessing of various processes, or γ: combinations thereof. Theprocessor includes a CPU and a memory such as a RAM and a ROM, and thememory stores a program code or an instruction configured to cause theCPU to execute a process. The memory, i.e. a computer-readable medium,includes any readable medium that can be accessed by a general-purposeor dedicated computer.

The server 50 includes the control unit 51 and the storage unit 52. Thecontrol unit 51 is, for example, the CPU described above. The storageunit 52 is, for example, the memory described above.

Upon receiving the data from the information processing device 30, thecontrol unit 51 causes the data to be stored in the storage unit 52. Forexample, upon receiving the data set 46 from the information processingdevice 30, the control unit 51 causes the data set 46 to be stored inthe storage unit 52. In this manner, the control unit 51 accumulates thedata in the storage unit 52. By accumulating data in the storage unit52, so-called big data 53 is configured.

Upon receiving the post-printing image data and the original image datatransmitted from the information processing device 30, the control unit51 performs image analysis to quantify the image quality of the image.The control unit 51 quantifies the image quality of the post-printingimage data with respect to the original image data by analyzing thereceived post-printing image data and the original image data. Thecontrol unit 51 quantifies the image quality by the Fast FourierTransform, for example. When the image data is in a full color, thecontrol unit 51 performs the Fast Fourier Transform on primary colors,for example.

The post-printing image data is data obtained by digitization at aresolution that is greater than or equal to the resolution of the imagedrawn on the fabric 99. In other words, deterioration of the imagequality is suppressed when capturing the fabric 99 as an image for thepost-printing image data. Therefore, the image quality of thepost-printing image data can be appropriately quantified.

The control unit 51 performs operation along a flowchart illustrated inFIG. 5 , for example, when the data set 46 is received. The series ofprocesses illustrated in FIG. 5 is a process for analyzing the imagedata.

As illustrated in FIG. 5 , in step S31, the control unit 51 firstgenerates analysis image data from the post-printing image data and theoriginal image data. The control unit 51 generates the analysis imagedata by, for example, taking a luminance difference between thepost-printing image data and the original image data for eachcorresponding pixel. This results in the analysis image data that doesnot affect an image design. The luminance is expressed, for example, inthe Lab color system.

The analysis image data indicates a change in the image quality betweenthe original image data and the post-printing image data. That is, theanalysis image data represents the image quality of the post-printingimage data based on the original image data. Therefore, by analyzing theanalysis image data, it is possible to evaluate how much the imagequality of the post-printing image data has changed relative to theoriginal image data. That is, the degree of the deterioration of theimage quality can be evaluated.

The control unit 51 performs a Fourier transform on the analysis imagedata in step S32. At this time, the control unit 51 performs the Fouriertransform on two directions in a vertical direction and a horizontaldirection with the luminance as an amplitude. As a result, a spectrumsuch as, for example, a power spectrum, a Wiener spectrum, etc. areobtained for the analysis image data.

In step S33, the control unit 51 quantifies the image quality of thepost-printing image data as an image quality parameter by analyzing thespectrum. Examples of the image quality include black concentration,gamut, strikethrough, bleeding, sharpness, color taste, granularity,banding, gradation, etc. An indicator value indicating such imagequality is correlated with the spectrum obtained in step S32. Forexample, when banding occurs, an indicator value indicating the bandingis represented in the spectrum. For example, as for granularity, anindicator value indicating the granularity is represented in thespectrum.

The control unit 51 determines the indicator value to be an indicator ofthe banding based on, for example, the power spectrum of the analysisimage data and a predetermined correction function that corrects thevisual sensitivity. The control unit 51 determines the indicator valueto be an indicator of granularity based on, for example, a predeterminedcorrection function for correcting the luminous sensitivity and theWiener spectrum of the analysis image data. The control unit 51evaluates the banding and granularity, for example, by comparing theobtained indicator value with a reference value thereof. In this manner,the control unit 51 quantifies the image quality of the post-printingimage data as an image quality parameter. As a result, the image qualityof the post-printing image data with regard to the original image datais evaluated by an objective indicator.

In step S34, the control unit 51 stores the image quality parameter inthe storage unit 52. Specifically, the control unit 51 associates theimage quality parameter obtained in step S33 with the post-printingimage data and the original image data that triggered the start of theprocess illustrated in FIG. 5 , and stores the image quality parameterin the storage unit 52. In other words, the control unit 51 accumulatesthe image quality of the post-printing image data in a state of beingquantified as an image quality parameter in the storage unit 52. Assuch, the image quality parameter constitutes the big data 53.

Upon terminating the process in step S34, the control unit 51 terminatesthe series of processes illustrated in FIG. 5 . Next, the generation ofthe derivation data 47 by the server 50 will be described. The server 50may transmit the generated derivation data 47 to the informationprocessing device 30. In this case, the derivation data 47 stored in thestorage unit 35 of the information processing device 30 can be updated.

The control unit 51 may generate the derivation data 47 defining alearned model that derives the recommended parameter from the imagequality parameter, for example, from the big data 53 stored in thestorage 52.

For example, the control unit 51 inputs the large amount of thepost-printing image data, the original image data, the image qualityparameters and printing parameters stored in the storage unit 52 assupervised data into the model. This causes the model to learn thecorrelation between the post-printing image data and the original imagedata, the image quality parameter, and the printing parameter. Thereby,the relationship between the post-printing image data and the originalimage data, and the printing parameter recommended for obtaining thepredetermined image quality, that is, the recommended parameter, isfound. Examples of learning techniques include, for example, deeplearning. Such learning results in a learned model that outputs theprinting parameter recommended for obtaining predetermined image qualitywhen the post-printing image data and the original image data are input.

The image quality parameter is a parameter that indicates the differencebetween the image quality of the post-printing image data and the imagequality of the original image data. Therefore, when the post-printingimage data and the original image data are input, the learned modeloutputs a printing parameter such that the difference in image qualitybetween the two is small, for example, the image quality parameter isless than or equal to a predetermined value. In this manner, the controlunit 51 may generate a learned model that outputs the printing parameterrecommended for bringing the image quality of the image drawn on thefabric 99 closer to the image quality of the original image data. Forexample, the control unit 51 may generate a learned model that outputsthe printing parameter recommended for obtaining the image qualityequivalent to the original image data, and may generate a learned modelthat outputs the printing parameter recommended for keeping the changein the image quality with respect to the original image data within apredetermined value.

The control unit 51 changes data used for learning from the big data 53,depending on the purpose of the learned model. In other words, thecontrol unit 51 changes the data used for learning in accordance withinput variables input to the learned model and output variables outputby the learned model. The data used for learning of the big data 53 isoptional. Accordingly, various learned models can be generated from thebig data 53.

The derivation data 47 may be data defining an analysis model obtainedby multivariate analysis. The control unit 51 can generate thederivation data 47 defining such an analysis model. In this case, thecontrol unit 51 performs the multivariate analysis on the large amountof data accumulated in the storage unit 52. The control unit 51 performsthe multivariate analysis on, for example, the image quality parameterand the printing parameter. The control unit 51 may perform themultivariate analysis on the data set 46.

One example of the multivariate analysis includes an MT method. First,from the large amount of data, a population, i.e., unit space, iscreated in which the image quality of the post-printing image data isgreater than or equal to predetermined image quality. Then, theMahalanobis distance to the unit space is calculated. As a result, thecorrelation between the image quality parameter and other data can begasped. The greater the Mahalanobis distance, the lower the imagequality. Next, the threshold value of the Mahalanobis distance withrespect to the unit space is determined. This results in the analysismodel. According to this analysis model, the correlation between theimage quality parameter and the printing parameter recommended forobtaining desired image quality, that is, the recommended parameter, canbe found. Thus, an analysis model is obtained that derives therecommended parameter from the image quality parameter, i.e. from thepost-printing image data and the original image data. Thus, in thiscase, the server 50 may transmit the image quality parameter of thepost-printing image data to the information processing device 30.Further, the information processing device 30 may obtain the imagequality parameter by quantifying the image quality of the post-printingimage data with regard to the original image data. In this manner, theinformation processing device 30 can derive the recommended parameterfrom the post-printing image data and the original image data based onthe deriving data 47.

Next, the functions and effects of the information processing device 30will be described.

(1) The information processing device 30 includes the acquisition unit33 configured to acquire the post-printing image data and the originalimage data, the storage unit 35 configured to store the derivation data47 indicating the correspondence relationship between the post-printingimage data and the original image data, and the recommended parameterfor at least one of the pre-processing device 11 and the post-processingdevice 13, and the control unit 34 configured to derive the recommendedparameter based on the post-printing image data, the original imagedata, and the derivation data 47.

According to this configuration, the information processing device 30can provide the user with the recommended parameter for at least one ofthe pre-processing device 11 and the post-processing device 13 based onthe printing image data and the original image data. The user can bringthe image quality of the image drawn on the fabric 99 closer to theimage quality of the original image data by setting the recommendedparameter for at least one of the pre-processing device 11 and thepost-processing device 13 in the device. This makes the user's workeasier.

(2) The post-printing image data is data obtained by digitization at aresolution that is greater than or equal to the resolution of the image.

According to this configuration, it is possible to obtain the image datasuitable for obtaining the image quality parameter indicating the imagequality of the post-printing image data with regard to the originalimage data. In other words, deterioration of the image quality issuppressed when capturing the fabric 99 as an image, so that the server50 can perform accurate image analysis.

(3) The post-printing image data includes the data obtained bydigitizing the front surface of the fabric 99 and the data obtained bydigitizing the back surface of the fabric 99.

For example, the absence of ink strikethrough is important in the imagequality. Thus, according to this configuration, it is possible to obtainthe image data suitable for obtaining the image quality parameterindicating the image quality of the post-printing image data with regardto the original image data. In other words, the accurate image analysiscan be performed by the server 50 in order to confirm the strikethroughof the ink discharged to the fabric 99.

(4) The post-printing image data includes the data obtained bydigitizing the fabric 99 in a state where the fabric 99 is stretched andthe data obtained by digitizing the fabric 99 in a state where thefabric 99 is not stretched.

For example, it is important in the image quality that the strikethroughof the ink does not occur in a state where the fabric 99 is stretched.Thus, according to this configuration, it is possible to obtain theimage data suitable for obtaining the image quality parameter indicatingthe image quality of the post-printing image data with regard to theoriginal image data. In other words, the image analysis with accuracycan be performed by the server 50 in order to confirm the picture in astate where the fabric 99 is stretched.

The present exemplary embodiment described above may be modified asfollows. The present exemplary embodiment described above and themodified examples below may be implemented in combination within a rangein which a technical contradiction does not arise.

-   -   The derivation data 47 may be data for deriving the recommended        parameter based on the post-printing image data, the original        image data, and the device data. For example, the input        variables of the learned model defined by the derivation data 47        may include device data. In this case, the control unit 51 uses        the device data for learning to generate the learned model. The        analysis model defined by the derivation data 47 is obtained by        performing the multivariate analysis on the device data in        addition to the image quality parameter and the printing        parameter.

According to this modification, the following effects are obtained.

(5) The control unit 34 can derive the recommended parameter for atleast one of the pre-processing device 11 and the post-processing device13 based on the image data, the original image data, and the devicedata.

-   -   A program causing a computer to process information about the        printing process may be distributed and sold, e.g., in a stored        state in a storage medium, or distributed and sold over a        communication line.    -   In addition to the information processing device 30, a control        device for controlling the printing system 10 may be provided.        In this case, the user controls the printing system 10 through        the control device based on the information provided by the        information processing device 30.    -   The data set 46 may include evaluation data indicating        information regarding the evaluation of the client relative to        the image quality of the post-printing image. By generating the        derivation data 47 from the data set 46 including the evaluation        data, the client's criteria for the image quality can be        grasped.    -   The image capturing device 41 may be incorporated into the        printing system 10. For example, the image capturing device 41        may be controlled by the information processing device 30.

Hereinafter, technical concepts and effects thereof that are understoodfrom the above-described exemplary embodiments and modified exampleswill be described.

(A) The information processing device includes an information processingdevice configured to process information related to a printing processperformed by an inkjet device and at least one of a pre-processingdevice and a post-processing device, the inkjet device being configuredto draw an image by discharging ink onto a fabric, the pre-processingdevice being configured to perform pre-processing on the fabric beforean image is drawn, the post-processing device being configured toperform post-processing on the fabric after an image is drawn, theinformation processing device including an acquisition unit configuredto acquire image data and original image data, the image data beingobtained by digitizing, as an image, the fabric on which the printingprocess is performed, the original image data being original data of animage drawn on the fabric, a storage unit configured to store derivationdata for deriving, based on the image data and the original image data,a recommended parameter for at least one of the pre-processing deviceand the post-processing device, and a control unit configured to derive,based on the derivation data, the recommended parameter from the imagedata and the original image data.

According to this configuration, the information processing device canprovide the user with the recommended parameter for at least one of thepre-processing device and the post-processing device based on the imagedata and the original image data. The user can bring the image qualityof the image drawn on the fabric closer to the image quality of theoriginal image data by setting the recommended parameter for at leastone of the pre-processing device and the post-processing device in thedevice. This makes the user's work easier.

(B) In the information processing device described above, the image datamay be data obtained by digitization at a resolution that is greaterthan or equal to a resolution of an image drawn on the fabric.

According to this configuration, the image data suitable for obtainingthe recommended parameter can be obtained.

(C) In the information processing device described above, the image datamay include data obtained by digitizing a front surface of the fabricand data obtained by digitizing a back surface of the fabric.

According to this configuration, the image data suitable for obtainingthe recommended parameter can be obtained.

(D) In the information processing device described above, the image datamay include data obtained by digitizing the fabric in a state of beingstretched and data obtained by digitizing the fabric in a state of beingnot stretched.

According to this configuration, the image data suitable for obtainingthe recommended parameter can be obtained.

(E) In the information processing device, the acquisition unit may beconfigured to acquire at least one of device data indicating deviceinformation of the pre-processing device and device data indicatingdevice information of the post-processing device, the derivation datamay be data for deriving the recommended parameter for at least one ofthe pre-processing device and the post-processing device based on theimage data, the original image data, and the device data, and thecontrol unit may be configured to derive, based on the derivation data,the recommended parameter from the image data, the original image data,and the device data.

According to this configuration, the control unit can derive therecommended parameter for at least one of the pre-processing device andthe post-processing device based on the image data, the original imagedata, and the device data.

(F) The information processing method includes an information processingmethod for processing information related to a printing processperformed by an inkjet device and at least one of a pre-processingdevice and a post-processing device, the inkjet device being configuredto draw an image by discharging ink onto a fabric, the pre-processingdevice being configured to perform pre-processing on the fabric beforean image is drawn, the post-processing device being configured toperform post-processing on the fabric after an image is drawn, themethod including acquiring image data and original image data, the imagedata being obtained by digitizing, as an image, the fabric on which theprinting process is performed, the original image data being originaldata of an image drawn on the fabric, and deriving, based on derivationdata, a recommended parameter from the image data and the original imagedata, the derivation data being data for deriving, based on the imagedata and the original image data, the recommended parameter for at leastone of the pre-processing device and the post-processing device.

According to this method, the same effect as that of the informationprocessing device described above can be obtained.

(G) The non-transitory computer-readable storage medium includes anon-transitory computer-readable storage medium storing a program forcausing a computer to process information related to a printing processperformed by an inkjet device and at least one of a pre-processingdevice and a post-processing device, the inkjet device being configuredto draw an image by discharging ink onto a fabric, the pre-processingdevice being configured to perform pre-processing on the fabric beforean image is drawn, the post-processing device being configured toperform post-processing on the fabric after an image is drawn, whereinthe program causes the computer to acquire image data and original imagedata, the image data being obtained by digitizing, as an image, thefabric on which the printing process is performed, the original imagedata being original data of an image drawn on the fabric, and derive,based on derivation data, a recommended parameter from the image dataand the original image data, the derivation data being data forderiving, based on the image data and the original image data, therecommended parameter for at least one of the pre-processing device andthe post-processing device.

According to this program, the same effect as that of the informationprocessing device described above can be obtained.

What is claimed is:
 1. An information processing device configured toprocess information related to a printing process performed by an inkjetdevice and at least one of a pre-processing device and a post-processingdevice, the inkjet device being configured to draw an image bydischarging ink onto a fabric, the pre-processing device beingconfigured to perform pre-processing on the fabric before an image isdrawn, the post-processing device being configured to performpost-processing on the fabric after an image is drawn, the informationprocessing device comprising: an acquisition unit configured to acquireimage data and original image data, the image data being obtained bydigitizing, as an image, the fabric on which the printing process isperformed, the original image data being original data of an originalimage drawn on the fabric; a storage unit configured to store derivationdata for deriving, based on the image data and the original image data,a recommended parameter for at least one of the pre-processing deviceand the post-processing device; a control unit configured to derive,based on the derivation data, the recommended parameter from the imagedata and the original image data; and an output unit for providing therecommended parameter to the at least one of the pre-processing deviceand the post-post processing device to thereby cause the at least one ofthe pre-processing device and the post-post processing device to performpre-processing or post-processing on the fabric configured to bring theimage drawn by the inkjet device closer to the original image.
 2. Theinformation processing device according to claim 1, wherein the imagedata is data obtained by digitization at a resolution that is greaterthan or equal to a resolution of an image drawn on the fabric.
 3. Theinformation processing device according to claim 1, wherein the imagedata includes data obtained by digitizing a front surface of the fabricand data obtained by digitizing a back surface of the fabric.
 4. Theinformation processing device according to claim 1, wherein the imagedata includes data obtained by digitizing the fabric in a state of beingstretched and data obtained by digitizing the fabric in a state of beingnot stretched.
 5. The information processing device according to claim1, wherein the acquisition unit is configured to acquire at least one ofdevice data indicating device information of the pre-processing deviceand device data indicating device information of the post-processingdevice, the derivation data is data for deriving the recommendedparameter for at least one of the pre-processing device and thepost-processing device based on the image data, the original image data,and the device data, and the control unit is configured to derive, basedon the derivation data, the recommended parameter from the image data,the original image data, and the device data.
 6. An informationprocessing method for processing information related to a printingprocess performed by an inkjet device and at least one of apre-processing device and a post-processing device, the inkjet devicebeing configured to draw an image by discharging ink onto a fabric, thepre-processing device being configured to perform pre-processing on thefabric before an image is drawn, the post-processing device beingconfigured to perform post-processing on the fabric after an image isdrawn, the method comprising: acquiring image data and original imagedata, the image data being obtained by digitizing, as an image, thefabric on which the printing process is performed, the original imagedata being original data of an original image drawn on the fabric;deriving, based on derivation data, a recommended parameter from theimage data and the original image data, the derivation data being datafor deriving, based on the image data and the original image data, therecommended parameter for at least one of the pre-processing device andthe post-processing device; and providing the recommended parameter tothe at least one of the pre-processing device and the post-postprocessing device to thereby cause the at least one of thepre-processing device and the post-post processing device to performpre-processing or post-processing on the fabric configured to bring theimage drawn by the inkjet device closer to the original image.
 7. Anon-transitory computer-readable storage medium storing a program forcausing a computer to process information related to a printing processperformed by an inkjet device and at least one of a pre-processingdevice and a post-processing device, the inkjet device being configuredto draw an image by discharging ink onto a fabric, the pre-processingdevice being configured to perform pre-processing on the fabric beforean image is drawn, the post-processing device being configured toperform post-processing on the fabric after an image is drawn, whereinthe program causes the computer to: acquire image data and originalimage data, the image data being obtained by digitizing, as an image,the fabric on which the printing process is performed, the originalimage data being original data of an original image drawn on the fabric;derive, based on derivation data, a recommended parameter from the imagedata and the original image data, the derivation data being data forderiving, based on the image data and the original image data, therecommended parameter for at least one of the pre-processing device andthe post-processing device; and provide the recommended parameter to theat least one of the pre-processing device and the post-post processingdevice to thereby cause the at least one of the pre-processing deviceand the post-post processing device to perform pre-processing orpost-processing on the fabric configured to bring the image drawn by theinkjet device closer to the original image.